Strategic Customer Recommendations in Online Service Platform

45 Pages Posted: 26 May 2020

See all articles by Ailing Xu

Ailing Xu

Southern University of Science and Technology

Wei You

Hong Kong University of Science and Technology

Xiang Zhong

University of Florida - College of Engineering

Qiao-Chu He

Southern University of Science and Technology

Date Written: April 18, 2020

Abstract

In online service platforms, economic inefficiency arises when customers are not fully aware of their preferences - customers may choose an unsuitable service among horizontally differentiated ones. With its expertise or data dominance, a platform can be more informed about customers’ hidden preferences and in turn, provide service consultations to customers. From a customer-centric perspective, we focus on the effects of service consultations on customers’ queue-joining behaviors and social welfare.

We propose a queueing game model wherein customers make Bayesian belief updates based on a platform’s recommendations, to decide between joining two horizontally differentiated queues. When the customers self-select their favorite service, their queue-joining behaviors impose negative externalities through congestion, which poses a welfare gap towards "the first best". Our results indicate that service consultations navigate the customers towards the more appropriate service, thus improving matching efficiency, reducing congestion cost and enhancing the total customer welfare. We further study how the platform should strategically release (partial) information by making personalized service recommendations to the customers. Surprisingly, we identify the "value of ignorance" when a customer-centric platform maximizes the aggregate customer welfare by strategically withholding service consultation results from a subset of the customers. These customers turn out to be the most flexible ones, who can correct the over-crowding queue-joining behaviors when set uninformed.

Keywords: service consultations, Hotelling model, Bayesian learning, game with incomplete information, targeted information disclosure

Suggested Citation

Xu, Ailing and You, Wei and Zhong, Xiang and He, Qiao-Chu, Strategic Customer Recommendations in Online Service Platform (April 18, 2020). Available at SSRN: https://ssrn.com/abstract=3583397 or http://dx.doi.org/10.2139/ssrn.3583397

Ailing Xu (Contact Author)

Southern University of Science and Technology ( email )

1088 Xueyuan Avenue
Shenzhen, Guangdong 518055
China

Wei You

Hong Kong University of Science and Technology ( email )

China

Xiang Zhong

University of Florida - College of Engineering ( email )

United States

Qiao-Chu He

Southern University of Science and Technology ( email )

No 1088, xueyuan Rd.
Xili, Nanshan District
Shenzhen, Guangdong 518055
China

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